Description
YACS was created as a lightweight library to define and manage
system configurations, such as those commonly found in software
designed for scientific experimentation. These "configurations"
typically cover concepts like hyperparameters used in training a
machine learning model or configurable model hyperparameters, such
as the depth of a convolutional neural network. Since you're doing
science, reproducibility is paramount and thus you need a reliable
way to serialize experimental configurations. YACS
uses YAML as a simple, human readable serialization format.
The paradigm is: your code + a YACS config for experiment E (+ external dependencies + hardware + other nuisance terms ...) = reproducible experiment E. While you might not be able to control
everything, at least you can control your code and your experimental
configuration. YACS is here to help you with that.
YACS grew out of the experimental configuration systems used in:
py-faster-rcnn and
Detectron.
yacs alternatives and similar packages
Based on the "Configuration" category.
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parse_it
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